#
#    QQ plot of smoothed residual field against model
#
#  qqplot.ppm()       QQ plot (including simulation)
#
#  $Revision: 1.31 $   $Date: 2020/11/18 03:07:14 $
#

qqplot.ppm <- local({

  ## How to refit the model
  refit <- function(fit, pattern) {
    update.ppm(fit, Q=pattern, use.internal=(fit$method != "mppm"))
  }
  
  ## how to compute the residual field
  residualfield <- function(fit, ...) {
    d <- diagnose.ppm(fit, which="smooth",
                      plot.it=FALSE, compute.cts=FALSE, compute.sd=FALSE,
                      check=FALSE, ...)
    return(d$smooth$Z$v)
  }

  qqplot.ppm <-
    function(fit, nsim=100, expr=NULL, ..., type="raw", style="mean",
             fast=TRUE, verbose=TRUE, plot.it=TRUE,
             dimyx=NULL, nrep=if(fast) 5e4 else 1e5,
             control=update(default.rmhcontrol(fit), nrep=nrep),
             saveall=FALSE,
             monochrome=FALSE,
             limcol=if(monochrome) "black" else "red",
             maxerr=max(100, ceiling(nsim/10)),
             check=TRUE, repair=TRUE, envir.expr) {
    verifyclass(fit, "ppm")

    if(check && damaged.ppm(fit)) {
      if(!repair)
        stop("object format corrupted; try update(fit, use.internal=TRUE)")
      message("object format corrupted; repairing it.")
      fit <- update(fit, use.internal=TRUE)
    }
  
    if(fast) {
      oldnpixel <- spatstat.options("npixel")
      if(is.null(dimyx)) 
        dimyx <- pmin(40, rev(oldnpixel))
      spatstat.options(npixel=rev(dimyx))
    } 
    
    ################   How to evaluate residuals ##########################
  
    ## Quantiles of the residual field will be computed.

    ## Data values
    dat <- residualfield(fit, type=type, ..., dimyx=dimyx)

    ##################  How to perform simulations?  #######################

    ## envir.call <- sys.parent()
    envir.here <- sys.frame(sys.nframe())

    ## extract.from.list <- FALSE
    inext <- 0 # to placate package checker
    dont.complain.about(inext)
    
    if(is.null(expr)) {
      ## We will simulate from the fitted model 'nsim' times
      ## and refit the model to these simulations
      simsource <- "fit"
      how.simulating <- "simulating from fitted model" 

      ## prepare rmh arguments
      rcontrol <- rmhcontrol(control)
      rmodel   <- rmhmodel(fit,
                           control=rcontrol, project=FALSE, verbose=verbose)
      rstart   <- rmhstart(n.start=data.ppm(fit)$n)
      ## pre-digest arguments
      rmhinfolist <- rmh(rmodel, rstart, rcontrol, preponly=TRUE, verbose=FALSE)
    
      ## expression to be evaluated each time
      expr <- expression(
        refit(fit, 
              rmhEngine(rmhinfolist, verbose=FALSE)))
      envir.expr <- envir.here

      ## pacify code checkers
      dont.complain.about(rmhinfolist)
    } else if(is.expression(expr)) {
      simsource <- "expr"
      how.simulating <- paste("evaluating", sQuote("expr"))  
      if(missing(envir.expr) || is.null(envir.expr))
        envir.expr <- parent.frame()
    } else if(inherits(expr, "envelope")) {
      simpat <- attr(expr, "simpatterns")
      if(!is.null(simpat) && all(sapply(simpat, is.ppp))) {
        expr <- expression(simpat[[inext]])
        envir.expr <- envir.here
        dont.complain.about(simpat)
        simsource <- "list"
        how.simulating <- "extracting point pattern from list"
      } else stop(paste("Argument", sQuote("expr"),
                        "is an envelope object,",
                        "but does not contain point patterns"),
                  call.=FALSE)
    } else if(is.list(expr) && all(sapply(expr, is.ppp))) {
      simpat <- expr
      expr <- expression(simpat[[inext]])
      envir.expr <- envir.here
      dont.complain.about(simpat)
      simsource <- "list"
      how.simulating <- "extracting point pattern from list"
    } else stop(paste(sQuote("expr"),
                      "should be an expression, or an envelope object,",
                      "or a list of point patterns"),
                call.=FALSE)

    exprstring <- if(simsource == "expr") deparse(expr) else NULL

    ######  Perform simulations
    if(verbose) {
      cat(paste("Simulating", nsim, "realisations... "))
      pstate <- list()
    }
    simul.sizes <- numeric(nsim)
    isim <- 0
    ierr <- 0
    repeat {
      inext <- isim + 1
      ## protect from randomly-generated crashes in gam
      ei <- try(eval(expr, envir=envir.expr), silent=!verbose)
      if(inherits(ei, "try-error")) {
        ## error encountered in evaluating 'expr'
        ierr <- ierr + 1
        if(ierr > maxerr) 
          stop(paste("Exceeded maximum of", maxerr,
                     "failures in", how.simulating,
                     "after generating only", isim, "realisations"))
        else break
      } else {
        ## simulation successful
        isim <- isim + 1
        fiti <- 
          if(simsource == "fit")
            ei
          else if(is.ppm(ei))
            ei
          else if(is.ppp(ei))
            refit(fit, ei)
          else
            stop("result of eval(expr) is not a ppm or ppp object")
        ## diagnostic info
        simul.sizes[isim] <- data.ppm(fiti)$n
        ## compute residual field
        resi <- residualfield(fiti, type=type, ..., dimyx=dimyx)
        if(isim == 1)
          sim <- array(, dim=c(dim(resi), nsim))
        sim[,,isim] <- resi
        if(verbose) 
          pstate <- progressreport(isim, nsim, state=pstate)
        if(isim >= nsim)
          break
      }
    }

    ###### Report diagnostics
    if(ierr > 0)
      cat(paste("\n\n**Alert:",
                ierr, "failures occurred in", how.simulating, "\n\n"))
    nempty <- sum(simul.sizes == 0)
    if(nempty > 0)
      cat(paste("\n\n**Alert:",
                nempty, "out of", nsim,
                "simulated patterns were empty.\n\n"))
    else
      cat(paste("\nDiagnostic info:\n",
                "simulated patterns contained an average of",
                mean(simul.sizes), "points.\n"))
    if(nempty == nsim)
      warning("All simulated patterns were empty")
    ############ Plot them
    switch(style,
           classical = {
             rr <- range(c(dat,sim))
             result <- qqplot(sim, dat, xlim=rr, ylim=rr, asp=1.0,
                              xlab="Quantiles of simulation",
                              ylab="Quantiles of data",plot.it=plot.it)
             title(sub=paste("Residuals:", type))
             abline(0,1, lty=2)
             result <- append(result,
                              list(data=dat,
                                   sim=sim,
                                   xlim=rr,
                                   ylim=rr,
                                   xlab="Quantiles of simulation",
                                   ylab="Quantiles of data",
                                   rtype=type,
                                   nsim=nsim,
                                   fit=fit,
                                   expr=exprstring,
                                   simsource = simsource
                                   )
                              )
           },
           mean = {
             ## compute quantiles corresponding to probabilities p[i]
             ## separately in each realisation.
             if(verbose) cat("Calculating quantiles...")
             if(fast) {
               p <- ppoints(min(100,length(dat)), 3/8)
               qsim <- apply(sim, 3, quantile, probs=p, na.rm=TRUE)
             } else {
               qsim <- apply(sim, 3, sort, na.last=TRUE)
             }
             if(verbose) cat("averaging...")
             ## sample mean of each quantile
             meanq <- apply(qsim, 1, mean, na.rm=TRUE)
             ## et cetera
             varq <- apply(qsim, 1, var, na.rm=TRUE)
             sdq <- sqrt(varq)
             q.025 <- apply(qsim, 1, quantile, probs=0.025, na.rm=TRUE)
             q.975 <- apply(qsim, 1, quantile, probs=0.975, na.rm=TRUE)
  
             rr <- range(c(meanq,dat), na.rm=TRUE)

             dats <- if(fast) quantile(dat, probs=p, na.rm=TRUE) else
                              sort(dat, na.last=TRUE)

             if(verbose) cat("..Done.\n")
             if(plot.it) {
               plot(meanq, dats,
                    xlab="Mean quantile of simulations", ylab="data quantile",
                    xlim=rr, ylim=rr, asp=1.0)
               abline(0,1)
               lines(meanq, q.025, lty=2, col=limcol)
               lines(meanq, q.975, lty=2, col=limcol)
               title(sub=paste("Residuals:", type))
             }
             result <- list(x=meanq, y=dats, sdq=sdq,
                            q.025=q.025, q.975=q.975,
                            data=dat, sim=sim,
                            xlim=rr, ylim=rr,
                            xlab="Mean quantile of simulations",
                            ylab="data quantile",
                            rtype=type,
                            nsim=nsim,
                            fit=fit,
                            expr=exprstring,
                            simsource=simsource)
           },
           stop(paste("Unrecognised option for", sQuote("style")))
           )

    ## Throw out baggage if not wanted         
    if(!saveall) {
      result$fit <- summary(fit, quick=TRUE)
      result$sim <- NULL
    }
         
    ## reset npixel
    if(fast)
      spatstat.options(npixel=oldnpixel)
    ##
    class(result) <- c("qqppm", class(result))
    return(invisible(result))
  }

  qqplot.ppm

})


plot.qqppm <- local({

  plot.qqppm <- function(x, ..., limits=TRUE,
                         monochrome=spatstat.options('monochrome'),
                         limcol=if(monochrome) "black" else "red") {
    stopifnot(inherits(x, "qqppm"))
    default.type <- if(length(x$x) > 150) "l" else "p"
    do.call(myplot,
            resolve.defaults(list(quote(x), ..., type=default.type,
                                  limits=limits, limcol=limcol)))
    return(invisible(x))
  }

  myplot <- function(object,
                     xlab = object$xlab, ylab = object$ylab,
                     xlim = object$xlim, ylim = object$ylim,
                     asp = 1,
                     type = default.type,
                     ..., limits=TRUE, limcol="red") {
    plot(object$x, object$y, xlab = xlab, ylab = ylab,
         xlim = xlim, ylim = ylim, asp = asp, type = type, ...)
    abline(0, 1)
    
    if(limits) {
      if(!is.null(object$q.025))
        lines(object$x, object$q.025, lty = 2, col=limcol)
      if(!is.null(object$q.975))
        lines(object$x, object$q.975, lty = 2, col=limcol)
    }
    title(sub=paste("Residuals:", object$rtype))
  }

  plot.qqppm
})


print.qqppm <- function(x, ...) {
  stopifnot(inherits(x, "qqppm"))
  splat("Q-Q plot of point process residuals",
        "of type", sQuote(x$rtype), "\n",
        "based on", x$nsim, "simulations")
  simsource <- x$simsource
  if(is.null(simsource)) # old version
    simsource <- if(x$simulate.from.fit) "fit" else "expr"
  switch(simsource,
         fit = {
           fit  <- x$fit
           sumfit <- if(is.ppm(fit)) summary(fit, quick=TRUE)
                     else if(inherits(fit, "summary.ppm")) fit
                     else list(name="(unrecognised format)")
           splat("\nSimulations from fitted model:", sumfit$name)
         },
         expr = {
           splat("Simulations obtained by evaluating the following expression:")
           print(x$expr)
         },
         list = {
           splat("Simulated point patterns were provided in a list")
         })
  invisible(NULL)
}

